Now, we study the primal-dual problem which was firstly investigated
in [1]}. This typical structured primal-dual framework covers a widely class of convex
optimization problems and it has found many applications to image processing, machine learning
[1]}, [3]}, [4]}, [5]}, [6]}.
Based on the duality nature of this framework, we design a new stochastic primal-dual splitting method and research the ergodic convergence
of the primal-dual gap.
